Research prediction of based on Latent Markov model, only from to research conversation itself set out to predict user's next chaining user, can not catch users' real interest.
基于马尔科夫模型的浏览路径预测，仅仅从用户的浏览会话本身出发来预测用户下一步的链接，并不能捕获用户的真正兴趣所在。
According to the users navigation history and the concept relations living in the HowNet, a user interest forest model based on the relative relations of concepts is constructed.
根据用户的访问历史，利用知网建立基于概念关系的用户兴趣森林模型。
Model and the user is interested in the interest of users and the information model, the user interested in a direct impact on the model of personalized information services.
而用户兴趣模型正是用户和兴趣的信息模型，用户兴趣模型直接影响到个性化的信息服务。
Feature interest measure is introduced in the hybrid user model, which can reflect the degree of feature preference of users and obtain more accurate similarity between target user and the neighbors.
混合用户模型引入的特征兴趣度，反映了用户对特征的偏好程度，在计算用户之间相似度时更为准确。
Feature interest measure is introduced in the hybrid user model, which can reflect the degree of feature preference of users and obtain more accurate similarity between target user and the neighbors.
混合用户模型引入的特征兴趣度，反映了用户对特征的偏好程度，在计算用户之间相似度时更为准确。
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